Economics and Fairness
May 22-23, 2019
Cambridge MA
1585 Massachusetts Avenue, Cambridge, MA, USA
Event Contact
Ann Drobnis
adrobnis@cra.org
Event Type
2019 Events, 2019 Visioning Activities, Workshop
Event Category
Tags
AI, Alexa, algorithmic decision making, data driven, data science, economic inequality, economics, equity, fairness and accountability, IoT, machine learning, privacy
The Computing Community Consortium’s (CCC) Fairness and Accountability Task Force will hold a visioning workshop on Economics and Fairness, May 22-23, 2019 in Cambridge, Massachusetts. This workshop will bring together computer science researchers with backgrounds in algorithmic decision making, machine learning, and data science with policy makers, legal experts, economists, and business leaders to discuss methods to ensure economic fairness in a data-driven world.
The workshop will address five main areas:
Data Concentration
- Machine learning (ML), regression, etc. are essentially commodities; as a result, the data is the primary source of differentiation. Should we be concerned with the concentration of data in a small set of hands? If so, how do we guard against this?
Algorithmic Decision Making
- With many consequential decisions being delegated to algorithms, how do we ensure that such decisions comply with both the spirit and letter of the law, as well as with ethical/societal fairness considerations?
Algorithmic Recommendation
- In many settings algorithms make recommendations rather than decisions. How do humans interpret and make use of these recommendations? In particular, can the combination be worse than either one on its own? Particular focus will be paid to the following three domains: 1) Interaction between crime prediction and judicial decision making, 2) news feeds and misinformation, 3) marketing and consumer decisions (e.g, search by voice).
Implications for Platforms
- New technologies have disrupted traditional industries (taxi, hotel) by reducing barriers to entry and lowering the costs of search and coordination. The traditional structure made regulating them easier and ensuring that they complied with extant norms. The new forms disperse decision making (to various degrees). Who is responsible for ensuring compliance? If it is the platform, how can algorithms be used to ensure compliance with the law and/or norms. For example, how does AirBnB ensure compliance with fair housing? How does Uber ensure equality of earning opportunities for drivers?
Equality of Opportunity
- Much of the fairness discussion in the context of ML has been on fairness of outcomes with less attention paid to measuring equality of opportunity and/or ensuring access to opportunity. However, all three areas warrant consideration when discussing fairness. What constitutes fair equality of opportunity, and what role do algorithms play in ensuring economic equality through data driven decisions?
The goal of the workshop is to produce a report or white paper that articulates best practices and research challenges with regards to fairness and economics, as well as provides a sense of direction for the field. This workshop is by invitation only, but if you or someone you know is interested in participating, please email Ann Drobnis at adrobnis@cra.org for consideration.
May 22, 2019 (Wednesday)
07:30 AM | BREAKFAST |
08:30 AM | Welcome and Introductions |
08:45 AM | Economics View on Fairness
Mallesh Pai, Rice- “Can Free Markets lead to Fair Markets?” |
09:30 AM | Computer Science View on Fairness
Sharad Goel, Stanford– “The Measure and Mismeasure of Fairness: A Critical Review of Fair Machine Learning” |
10:15 AM | BREAK |
10:30 AM | Algorithm Decision Making
Prasanna Tambe, Wharton- “Artificial Intelligence in Human Resources Management: Challenges and a Path Forward” Lindsey Zuloaga, HierVue- “Algorithms for Hire” Bo Cowgill, Columbia- “Economics, Fairness and Algorithmic Bias” Discussant: Matt Weinberg, Princeton |
12:30 PM | LUNCH |
01:45 PM | Lightning Round / Rump Session |
02:30 PM | BREAK |
03:00 PM | Platforms
Daniel Knoefle, Uber- “Pricing Efficiently in Designed Markets: Evidence from Ride-Sharing” Karen Levy, Cornell University- “Trade-offs in Designing Against Discrimination” Mike Luca, HBS- “Discrimination in Online Marketplaces” Discussant: Ayelet Israeli, HBS |
05:00 PM | BREAK |
05:15 PM | Discussion/Synthesis |
06:30 PM | DINNER |
May 23, 2019 (Thursday)
07:30 AM | BREAKFAST |
08:50 AM | Algorithm Recommendations
Megan Stevenson, George Mason- “Algorithmic Risk Assessment in the Hands of Humans” Michael D. Ekstrand, Boise State- “Recommendations, Decisions, Feedback Loops, and Maybe Saving the Planet” Katrina Ligett, The Hebrew University of Jerusalem- “Humans and algorithms, deciding together” Discussant: Aaron Roth, University of Pennsylvania |
10:50 AM | BREAK |
11:00 AM | Lightning Round/Rump Session |
11:45 AM | LUNCH |
01:00 PM | Equality of Opportunity
John E. Roemer, Yale – “Equalizing Opportunities through policy: A primer.” Rediet Abebe, Cornell University – “Mechanism Design for Social Good” Discussant: Dirk Bergemann, Yale University |
03:00 PM | Working Session |
05:00 PM | Adjourn |
Organizing Committee:
David Parkes, Harvard University![]() |
Rakesh Vohra, University of Pennsylvania![]() |
The CCC will cover travel expenses for all participants who desire it. Participants are asked to make their own travel arrangements to get to the workshop, including purchasing airline tickets. Following the symposium, CCC will circulate a reimbursement form that participants will need to complete and submit, along with copies of receipts for amounts exceeding $75.
In general, standard Federal travel policies apply: CCC will reimburse for non-refundable economy airfare on U.S. Flag carriers; and no alcohol will be covered.
For more information, please see the Guidelines for Participant Reimbursements from CCC.
Additional questions about the reimbursement policy should be directed to Ann Drobnis, CCC Director (adrobnis [at] cra.org).